The present disclosure provides a method and a device for controlling an active distribution network, relating to the field of power system operation and control technology. The method includes: creating a power loss objective function; determining first power flow equations; obtaining second power flow equations by performing linearization on the first power flow equations; determining a sub-scale adjustment model of a transformer; obtaining a linearized model of the transformer by performing linearization on the sub-scale adjustment model; obtaining control parameters by solving the power loss objective function according to the second power flow equations, the linearized model of the transformer, an operation constraint of the continuous reactive power compensator, an operation constraint of the grouping switching capacitor, an operation constraint of the distributed generator and a safety operation constraint in the active distribution network, such that the active distribution network is controlled by the obtained parameters to minimize power loss.

A power converter and a method. When the voltage at the grid connection point exceeds the preset voltage range and an amplitude of a voltage output by the power conversion circuit is not greater than a voltage threshold, embodiments can control the amplitude of the current output by the power conversion circuit to be not greater than a second current threshold, where the second current threshold is greater than the first current threshold, and a ratio of an active current to a reactive current output by the power conversion circuit is constant or changes; or, when the amplitude of the voltage output by the power conversion circuit is greater than the voltage threshold, embodiments can control the amplitude of the current output by the power conversion circuit to be equal to the second current threshold, where the ratio of the active current to the reactive current changes.

The present invention relates to the technical field of power electronics converters and discloses a grid-forming energy storage converter on/off-grid switching control method and system, where the method includes the following steps: S1: using a single-loop power control strategy in an off-grid state when an on-grid relay of target energy storage drops out; S2: using a parallel virtual impedance loop-based power control strategy in a transient on-grid state when the on-grid relay of target energy storage pulls in; and S3: using a cascaded dual-loop power control strategy with a virtual admittance voltage loop and an inner current loop when a stable on-grid state is established. The present invention solves the problems of large current impact and unstable switching process state in the existing working strategy for on/off-grid switching in the prior art.

A control device with integrated energy conditioning and energy management for actuating an electrically operated and/or controlled actuator, including: a controller for generating an actuation signal for the actuator; a connection for connecting the control device to an external electrical energy supply that provides a grid voltage; a circuit arrangement for the conditioning, rectification and conversion of the grid voltage into a first intermediate circuit DC voltage, a level of which is independent of a level of the grid voltage; at least one electrical buffer store for the first intermediate circuit DC voltage for buffering a power necessary for maintaining a further voltage, derived from the first intermediate circuit DC voltage, for supplying power to the controller unit in the event of failure of the external electrical energy supply and for transferring the actuator to a safe state, for example upon failure of the external electrical energy supply.

A control method and system for automatic voltage control (AVC) substation reactive power optimization assistance are provided, and belong to the technical field of electric power system operation control. The method includes: determining whether a reactive integrated electric quantity of a main transformer step-down switch of a substation exceeds a set value of reactive integrated electric quantity of the main transformer step-down switch; if yes, determining whether voltage of a 10 kV bus of the substation is qualified; if yes, determining whether a power factor of a transformer step-down switch is greater than a power factor set value of the main transformer step-down switch; if yes, determining whether a reactive power demand of the substation is true; and if yes, putting a capacitor into use to perform reactive on-site balance control.

A power converter and a power converter control method. The power converter includes a three-phase inverter circuit and a controller, an input end of the three-phase inverter circuit is configured to connect to a direct current power supply, and a three-phase output end of the three-phase inverter circuit is configured to connect to a grid. The controller is configured to: when a target value of three-phase voltages output by the three-phase inverter circuit is greater than a voltage threshold, a value of a maximum phase voltage in the three-phase voltages output by the three-phase inverter circuit is greater than a first voltage value, a value of a minimum phase voltage in the three-phase voltages output by the three-phase inverter circuit is less than a second voltage value, and a positive-sequence component of the three-phase voltages is greater than a third voltage value.

An embodiment of the present disclosure provides a grid-forming inverter comprising: a power stage to convert electric power according to on/off controls of switching devices and to output the converted electric power to a grid; and a control circuit to calculate a frequency command value in proportion to a direct current input voltage and to control the switching devices using pulse width modulation (PWM) according to the frequency command value.

A converter circuit is configured to output a first reactive current to a power grid when a voltage value of an output port of the converter circuit decreases from a first working voltage value to a second working voltage value. The drive control circuit is configured to: in a process in which the converter circuit outputs the first reactive current to the power grid, when it is detected that the voltage value of the output port of the converter circuit increases to a third working voltage value and the third working voltage value is greater than or equal to a first recovery voltage value, control the converter circuit to output a second reactive current to the power grid, to recover the voltage value of the output port of the converter circuit to the first working voltage value.

An exemplary embodiment of the present disclosure provides a power converter system comprising a power converter. The power converter system can comprise a power converter electrically connected to a local power supply and an electrical utility grid. The power converter can comprise an output configured to exchange electrical power with the electrical utility grid. The power converter can be further configured to monitor one or more electrical parameters of the electrical utility grid over a period of time and alter one or more electrical parameters of the output of the power converter based on the monitored one or more electrical parameters of the electrical utility grid in real time using a deep learning neural network.

An exemplary embodiment of the present disclosure provides a power converter system comprising a power converter. The power converter system can comprise a power converter electrically connected to a local power supply and an electrical utility grid. The power converter can comprise an output configured to exchange electrical power with the electrical utility grid. The power converter can be further configured to monitor one or more electrical parameters of the electrical utility grid over a period of time and alter one or more electrical parameters of the output of the power converter based on the monitored one or more electrical parameters of the electrical utility grid in real time using a deep learning neural network.